Quantitative Methods for Behavioral Research

University Of Illinois Urbana-Champaign, Champaign IL

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Abstract

DESCRIPTION (provided by applicant): This program provides predoctoral (4 positions) and postdoctoral (3 positions) research training for psychologists specializing in research design, measurement, statistical methods, decision making, psychological scaling, and assessment of individual differences, with an emphasis on application of these methods in investigations of behavioral and mental disorders. During their careers these specialists (a) continue to train students in all areas of behavioral and social sciences by their research and teaching activities, and/or (b) act as principal investigators or consultants in research on basic processes, psychopathology, and related problems. Predoctoral trainees receive Ph.D. degrees in Psychology; some having joint majors in quantitative methods and substantive problem areas such as clinical, developmental, or cognitive psychology. Other trainees major in quantitative methods and receive M.S. degrees in Applied Statistics with specialization in psychological assessment, behavioral statistics (more broadly defined), and modeling with the aim of developing new methods, or improving existing methods for investigating psychological phenomena of all kinds, including basic cognitive, affective, social, and psychophysiological processes. Course and seminars are designed to advance trainees' knowledge of quantitative statistics that enables them to manipulate research data in psychologically meaningful ways. Research projects include: adolescent coping and neighborhood violence, social networks of at risk adolescent girls, reactions towards Arab Ethnic groups following the terrorist attacks on America, emotional and attentional mechanisms of high anxiety-sensitive individuals using fMRI neuroimaging and emotional Stroop paradigm, and cognitive and affective processes in pathological gambling. Research on methodological problems includes; effects of feedback on calibration, meta-analytic treatment of research results, alternatives to exploratory factor analysis, and models for the description and analysis of social networks.